Monthly Passenger Bus and Urban Transit Survey (MLUT)
Detailed information for January 2017
This survey is conducted by Statistics Canada in order to collect the necessary information to support the Integrated Business Statistics Program (IBSP). This survey collects data essential for the statistical analysis of the passenger bus industry and its impact on the Canadian economy. Your information may also be used by Statistics Canada for other statistical and research purposes.
Data release - March 31, 2017
This survey collects total operating revenues and passenger trip data from the largest urban and intercity passenger transit companies across Canada. Those companies represent 75% of provincial revenue for urban transit and intercity bus activity in Canada. These data are intended as a leading indicator of trends in the urban transit sector and are one input to monthly GDP estimates. Aggregate data nationally and by region will be made available.
This statistical activity is part of a set of surveys measuring various aspects of activities related to movement of people and goods. These surveys are grouped as follows:
Transportation by air includes records related to the movement of aircraft, passengers and cargo by air for both Canadian and foreign air carriers operating in Canada as well as the financial and operating characteristics of Canadian air carriers. These data are produced by the Aviation Statistics Centre.
Transportation by rail includes records relating to rail transportation in Canada and between the United States and Canada.
Transportation by road includes records relating to all road transport in Canada. In addition to surveying carriers and owners of registered motor vehicles, certain programs rely on aggregation of provincial and territorial administrative records.
Water Transport includes records relating to water transportation, domestic shipping, international seaborne shipping, and ports of loading and unloading.
Reference period: Month
Collection period: During the month following the reference month.
- Transportation by road
Data sources and methodology
The survey covers the operations of establishments which have urban and/or inter-city transit operations. An establishment is defined as the smallest reporting unit capable of reporting all elements of basic industrial statistics.
The questionnaire collects data on two variables: total operating revenues (excluding subsidies) and total number of passengers (passenger trips).
This is a sample survey with a cross-sectional design.
The sampling design of this survey is a stratified cut-off census of business establishments with a cross-sectional design with monthly follow-up. Data are collected for all units whose revenue exceeds the 25th percentile by industry and province. Survey specific fields on the Business Register are used to include targeted business establishments without a main business activity related to passenger bus transit.
The establishment is the statistical unit, while the enterprise is the sampling unit. An enterprise is a cluster of establishments.
Primary sampling strata are created using activity code (6 digit NAICS) and province.
SAMPLING AND SUB-SAMPLING
Within each given primary sampling stratum, all units whose revenue exceeds the 25th percentile of that stratum are selected. There is no sub-sampling.
Data collection for this reference period: 2017-02-15 to 2017-03-24
Responding to this survey is mandatory.
Data are collected directly from survey respondents.
Collection is done through an electronic questionnaire.
View the Questionnaire(s) and reporting guide(s) .
Edit rules at the micro-data level have been incorporated into the electronic questionnaire to ensure the submitted data are consistent as much as possible at the time of capture. Remaining inconsistencies will be corrected during the edit and imputation process. Other inconsistent data can be identified and corrected manually, after verification with the respondent.
Various methods for imputation, such as donor imputation, ratio analysis and trend analysis are utilized. Trends from tax data are also used when applicable.
This survey uses the Generalized Estimation System (G-Est) developed at Statistics Canada to produce its domain estimates and quality indicators. It is a SAS-based application for producing estimates for domains of a population based on a sample and auxiliary information. Estimates are computed at several levels of interest such as NAICS and province, based on the most recent classification information for the statistical entity and the survey reference period.
Population totals are calculated.
The subject matter analysts at Statistics Canada examine the data, verify the results, perform coherence analysis, study changes across cycles, and compare the results with other sources/surveys.
Statistics Canada is prohibited by law from releasing any information it collects which could identify any person, business, or organization, unless consent has been given by the respondent or as permitted by the Statistics Act. Various confidentiality rules are applied to all data that are released or published to prevent the publication or disclosure of any information deemed confidential. If necessary, data are suppressed to prevent direct or residual disclosure of identifiable data.
Data for a specific industry or variable may be suppressed (along with that of a second industry or variable) if the number of enterprises in the population is too low.
Revisions and seasonal adjustment
Monthly estimates are provided for the reference month. The data for previous months are revised if necessary. The data are not seasonally adjusted.
Quality ratings are derived from the sampling coefficient of variation and imputation rates.
Coverage rates are evaluated after the sampling process.
Non-sampling error is not related to sampling and may occur for many reasons. For example, non-response is an important source of non-sampling error. Population coverage issues, differences in the interpretation of questions, incorrect information from respondents, and mistakes in recording, coding and processing data are other examples of non-sampling errors.
Non-sampling errors are controlled through a careful design of the questionnaire, the use of a minimal number of simple concepts and consistency checks. Coverage error was minimized by using multiple sources to update the frame. Measures such as response rates are used as indicators of the possible extent of non-sampling errors.
In addition to increased variance, non-response can result in biased estimates if non-respondents have different characteristics from respondents. Non response is addressed through imputation and follow-up with respondents.
Coverage error is minimized by keeping the frame up to date using survey and administrative sources. Coverage rates are monitored during the sampling process.
OTHER NON-SAMPLING ERRORS
Basic analysis (e.g. percentage change) is used to ensure that there are no significant changes from month to month. When a significant change occurs, follow-up is undertaken to check the data. Seasonal variations are expected (e.g. a fall peak for urban transit).
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